Integrated network model provides new insights into castration-resistant prostate cancer

Castration-resistant prostate cancer (CRPC) is the main challenge for prostate cancer treatment. Recent studies have indicated that extending the treatments to simultaneously targeting different pathways could provide better approaches. To better understand the regulatory functions of different path...

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Main Authors:	Hu, Yanling, Gu, Yinmin, Wang, Huimin, Huang, Yuanjie, Zou, Yi Ming
Format:	Online
Language:	English
Published:	Nature Publishing Group 2015
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4658549/

id	pubmed-4658549
recordtype	oai_dc
spelling	pubmed-46585492015-11-30 Integrated network model provides new insights into castration-resistant prostate cancer Hu, Yanling Gu, Yinmin Wang, Huimin Huang, Yuanjie Zou, Yi Ming Article Castration-resistant prostate cancer (CRPC) is the main challenge for prostate cancer treatment. Recent studies have indicated that extending the treatments to simultaneously targeting different pathways could provide better approaches. To better understand the regulatory functions of different pathways, a system-wide study of CRPC regulation is necessary. For this purpose, we constructed a comprehensive CRPC regulatory network by integrating multiple pathways such as the MEK/ERK and the PI3K/AKT pathways. We studied the feedback loops of this network and found that AKT was involved in all detected negative feedback loops. We translated the network into a predictive Boolean model and analyzed the stable states and the control effects of genes using novel methods. We found that the stable states naturally divide into two obvious groups characterizing PC3 and DU145 cells respectively. Stable state analysis further revealed that several critical genes, such as PTEN, AKT, RAF, and CDKN2A, had distinct expression behaviors in different clusters. Our model predicted the control effects of many genes. We used several public datasets as well as FHL2 overexpression to verify our finding. The results of this study can help in identifying potential therapeutic targets, especially simultaneous targets of multiple pathways, for CRPC. Nature Publishing Group 2015-11-25 /pmc/articles/PMC4658549/ /pubmed/26603105 http://dx.doi.org/10.1038/srep17280 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Hu, Yanling Gu, Yinmin Wang, Huimin Huang, Yuanjie Zou, Yi Ming
spellingShingle	Hu, Yanling Gu, Yinmin Wang, Huimin Huang, Yuanjie Zou, Yi Ming Integrated network model provides new insights into castration-resistant prostate cancer
author_facet	Hu, Yanling Gu, Yinmin Wang, Huimin Huang, Yuanjie Zou, Yi Ming
author_sort	Hu, Yanling
title	Integrated network model provides new insights into castration-resistant prostate cancer
title_short	Integrated network model provides new insights into castration-resistant prostate cancer
title_full	Integrated network model provides new insights into castration-resistant prostate cancer
title_fullStr	Integrated network model provides new insights into castration-resistant prostate cancer
title_full_unstemmed	Integrated network model provides new insights into castration-resistant prostate cancer
title_sort	integrated network model provides new insights into castration-resistant prostate cancer
description	Castration-resistant prostate cancer (CRPC) is the main challenge for prostate cancer treatment. Recent studies have indicated that extending the treatments to simultaneously targeting different pathways could provide better approaches. To better understand the regulatory functions of different pathways, a system-wide study of CRPC regulation is necessary. For this purpose, we constructed a comprehensive CRPC regulatory network by integrating multiple pathways such as the MEK/ERK and the PI3K/AKT pathways. We studied the feedback loops of this network and found that AKT was involved in all detected negative feedback loops. We translated the network into a predictive Boolean model and analyzed the stable states and the control effects of genes using novel methods. We found that the stable states naturally divide into two obvious groups characterizing PC3 and DU145 cells respectively. Stable state analysis further revealed that several critical genes, such as PTEN, AKT, RAF, and CDKN2A, had distinct expression behaviors in different clusters. Our model predicted the control effects of many genes. We used several public datasets as well as FHL2 overexpression to verify our finding. The results of this study can help in identifying potential therapeutic targets, especially simultaneous targets of multiple pathways, for CRPC.
publisher	Nature Publishing Group
publishDate	2015
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4658549/
_version_	1613505613259603968

Integrated network model provides new insights into castration-resistant prostate cancer

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